Initially we used a hugging face dataset in parquet format and parsed it and created images out of the file. This was a great database nut after some trials we found out that for our purpose it wont be helpful.
It contained 18000+ images for 1000+ celebrities. Around 18 per person.
After realizing this we found another database in Kaggle with 18k+ images for 100 celebrities and we are going to use that for our purpose.
Kaggle Link : https://www.kaggle.com/datasets/hereisburak/pins-face-recognition
from EDA import EDA
eda = EDA("../dataset", "EDA")
eda.calculate_eda()
c:\Users\DELL\Desktop\Conestoga\AIML\FOML-FinalProject\WhoLooksLikeMe\WhoLooksLikeMe-Model\WLLM-Nikhil-Model-Classes-2\EDA.py:97: FutureWarning: Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect. sns.barplot(x=image_counts.index, y=image_counts.values, palette='viridis')
Personality with minimum images: lionel messi (86 images) Personality with maximum images: leonardo dicaprio (237 images)
c:\Users\DELL\Desktop\Conestoga\AIML\FOML-FinalProject\WhoLooksLikeMe\WhoLooksLikeMe-Model\WLLM-Nikhil-Model-Classes-2\EDA.py:177: FutureWarning: Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect. sns.barplot(x=list(type_counts.keys()), y=list(type_counts.values()), palette='Set2')
All EDA results have been saved in the output directory.
We created 2 classes
These two classes will do the following
from TrainTestSplitter import TrainTestSplitter
from DataPreparation import DataPreparation
from WLLMSimilarityCalculatorAdvancedCorrected import SimilarityCalculatorAdvancedCorrected2
from WLLMModel import WLLMModel
import os
from datetime import datetime
from WLLMModelLoader import WLLMModelLoader
#Dont edit this
modelname_prefix = "WLLM-Model-Selected"
username = input("Enter your name")
formatted_date = datetime.now().strftime("%m-%d-%H-%M")
sample_class_range= (50,102)
sample_class_range_name = "L2"
model_name = f"{modelname_prefix}-{username}-{sample_class_range_name}-{formatted_date}"
#TODO Point this to your repository of all images
original_data_dir = "../../../DontEditThese/Dataset3"
model_info_root_save_dir = "../SavedTrainingData/savedmodels"
dataset_dir = f"../TrainingDataImages/{model_name}" # Path to your dataset folder
savedmodels_dir = f"{model_info_root_save_dir}/{model_name}"
embeddings_dir = f"{model_info_root_save_dir}/{model_name}/embeddings"
# Check if the folder exists; if not, create it
if not os.path.exists(dataset_dir):
os.makedirs(dataset_dir)
# Check if the folder exists; if not, create it
if not os.path.exists(embeddings_dir):
os.makedirs(embeddings_dir)
# Check if the folder exists; if not, create it
if not os.path.exists(savedmodels_dir):
os.makedirs(savedmodels_dir)
#Copy sample class number of images from original repo to dataset_dir
data_preparation = DataPreparation(original_data_dir, dataset_dir, sample_range=sample_class_range)
selected_classes = data_preparation.prepare_data()
#Split data to train and test
splitter = TrainTestSplitter(dataset_dir)
splitter.create_train_test_split(test_file_count=4)
Please note that the ipynb file was created after all training and testing was done after a lot of experimentation. So some of the codeblocks are not executed due to time constraints.
We have saved the plots and calculated the time taken and saved it in csv files which will be attached and shown in the ipynb file.
The final model we chose is the InceptionV3 base model trained on ImageNet dataset.
The output is being read from a saved file.
file_path = '../../WhoLooksLikeMe-Model/SavedTrainingData/savedmodels/WLLM-Model-Nikhil-L2-12-10-01-24/ModelSummary.txt'
with open(file_path, 'r', encoding="utf-8") as file:
for line in file:
print(line.strip())
## Training the model
model = WLLMModel(dataset_dir, savedmodels_dir)
model.train_model(output_dir=savedmodels_dir, epochs=100, batch_size=32)

We trained 4 models
3 models were created with 10 celebrities trained per model
4th one a single model trained on 50 celebrities together.

Vertically seeping through the plot we can identify which personality is getting predicted more.
Horizontally seeping through the plot we can identify who is getting predicted wrong.
from ClassificationModel import ClassificationModel
large_model_path = "../SavedTrainingData/savedmodels/WLLM-Model-Nikhil-L2-12-10-01-24/best_model.keras"
names_csv_path = "../SavedTrainingData/savedmodels/WLLM-Model-Nikhil-L2-12-10-01-24/WLLM-Model-Nikhil-L2-12-10-01-24.csv"
image_dataset_path = "../dataset"
predictions_save_path = "../predictions/model52"
classificationModel = ClassificationModel(large_model_path, names_csv_path)
Embedding model created using layer: 'embedding'.
classificationModel.evaluate_and_print_images("../TrainingDataImages/WLLM-Model-Nikhil-L2-12-10-01-24/test")
Found 208 images belonging to 52 classes.
c:\Users\DELL\Desktop\Conestoga\AIML\FOML-FinalProject\WhoLooksLikeMe\venv\tensorflow_facenet\Lib\site-packages\keras\src\trainers\data_adapters\py_dataset_adapter.py:121: UserWarning: Your `PyDataset` class should call `super().__init__(**kwargs)` in its constructor. `**kwargs` can include `workers`, `use_multiprocessing`, `max_queue_size`. Do not pass these arguments to `fit()`, as they will be ignored. self._warn_if_super_not_called()
52/52 ━━━━━━━━━━━━━━━━━━━━ 15s 246ms/step
| accuracy | precision | recall | f1-score | support | |
|---|---|---|---|---|---|
| johnny depp | 0.50 | 0.500000 | 0.500000 | 0.500000 | 4.000000 |
| josh radnor | 0.75 | 0.600000 | 0.750000 | 0.666667 | 4.000000 |
| katharine mcphee | 0.50 | 1.000000 | 0.500000 | 0.666667 | 4.000000 |
| katherine langford | 1.00 | 1.000000 | 1.000000 | 1.000000 | 4.000000 |
| keanu reeves | 1.00 | 1.000000 | 1.000000 | 1.000000 | 4.000000 |
| kiernen shipka | 0.75 | 1.000000 | 0.750000 | 0.857143 | 4.000000 |
| krysten ritter | 1.00 | 0.800000 | 1.000000 | 0.888889 | 4.000000 |
| leonardo dicaprio | 0.50 | 1.000000 | 0.500000 | 0.666667 | 4.000000 |
| lili reinhart | 0.75 | 0.428571 | 0.750000 | 0.545455 | 4.000000 |
| lindsey morgan | 0.75 | 0.600000 | 0.750000 | 0.666667 | 4.000000 |
| lionel messi | 0.50 | 1.000000 | 0.500000 | 0.666667 | 4.000000 |
| logan lerman | 0.25 | 0.500000 | 0.250000 | 0.333333 | 4.000000 |
| madelaine petsch | 0.50 | 0.666667 | 0.500000 | 0.571429 | 4.000000 |
| maisie williams | 0.25 | 0.500000 | 0.250000 | 0.333333 | 4.000000 |
| margot robbie | 0.50 | 0.400000 | 0.500000 | 0.444444 | 4.000000 |
| maria pedraza | 0.50 | 0.500000 | 0.500000 | 0.500000 | 4.000000 |
| marie avgeropoulos | 1.00 | 1.000000 | 1.000000 | 1.000000 | 4.000000 |
| mark ruffalo | 0.75 | 0.428571 | 0.750000 | 0.545455 | 4.000000 |
| mark zuckerberg | 1.00 | 1.000000 | 1.000000 | 1.000000 | 4.000000 |
| megan fox | 0.75 | 1.000000 | 0.750000 | 0.857143 | 4.000000 |
| melissa fumero | 0.75 | 0.750000 | 0.750000 | 0.750000 | 4.000000 |
| miley cyrus | 0.50 | 0.285714 | 0.500000 | 0.363636 | 4.000000 |
| millie bobby brown | 0.50 | 0.500000 | 0.500000 | 0.500000 | 4.000000 |
| morena baccarin | 0.75 | 1.000000 | 0.750000 | 0.857143 | 4.000000 |
| morgan freeman | 1.00 | 1.000000 | 1.000000 | 1.000000 | 4.000000 |
| nadia hilker | 1.00 | 0.666667 | 1.000000 | 0.800000 | 4.000000 |
| natalie dormer | 0.50 | 0.400000 | 0.500000 | 0.444444 | 4.000000 |
| natalie portman | 0.50 | 0.666667 | 0.500000 | 0.571429 | 4.000000 |
| neil patrick harris | 0.75 | 0.750000 | 0.750000 | 0.750000 | 4.000000 |
| pedro alonso | 0.75 | 0.750000 | 0.750000 | 0.750000 | 4.000000 |
| penn badgley | 0.75 | 0.750000 | 0.750000 | 0.750000 | 4.000000 |
| rami malek | 0.75 | 0.500000 | 0.750000 | 0.600000 | 4.000000 |
| rebecca ferguson | 0.75 | 1.000000 | 0.750000 | 0.857143 | 4.000000 |
| richard harmon | 0.75 | 0.750000 | 0.750000 | 0.750000 | 4.000000 |
| rihanna | 0.75 | 1.000000 | 0.750000 | 0.857143 | 4.000000 |
| robert de niro | 0.75 | 1.000000 | 0.750000 | 0.857143 | 4.000000 |
| robert downey jr | 1.00 | 0.666667 | 1.000000 | 0.800000 | 4.000000 |
| sarah wayne callies | 1.00 | 0.800000 | 1.000000 | 0.888889 | 4.000000 |
| scarlett johansson | 0.50 | 0.500000 | 0.500000 | 0.500000 | 4.000000 |
| selena gomez | 0.50 | 0.500000 | 0.500000 | 0.500000 | 4.000000 |
| shakira isabel mebarak | 0.50 | 0.666667 | 0.500000 | 0.571429 | 4.000000 |
| sophie turner | 1.00 | 0.800000 | 1.000000 | 0.888889 | 4.000000 |
| stephen amell | 0.75 | 1.000000 | 0.750000 | 0.857143 | 4.000000 |
| taylor swift | 0.25 | 0.500000 | 0.250000 | 0.333333 | 4.000000 |
| tom cruise | 0.50 | 0.666667 | 0.500000 | 0.571429 | 4.000000 |
| tom ellis | 0.75 | 0.600000 | 0.750000 | 0.666667 | 4.000000 |
| tom hardy | 1.00 | 1.000000 | 1.000000 | 1.000000 | 4.000000 |
| tom hiddleston | 0.25 | 1.000000 | 0.250000 | 0.400000 | 4.000000 |
| tom holland | 0.25 | 0.250000 | 0.250000 | 0.250000 | 4.000000 |
| tuppence middleton | 1.00 | 1.000000 | 1.000000 | 1.000000 | 4.000000 |
| ursula corbero | 1.00 | 0.571429 | 1.000000 | 0.727273 | 4.000000 |
| wentworth miller | 0.75 | 0.750000 | 0.750000 | 0.750000 | 4.000000 |
| accuracy | 0.00 | 0.692308 | 0.692308 | 0.692308 | 0.692308 |
| macro avg | 0.00 | 0.730082 | 0.692308 | 0.689867 | 208.000000 |
| weighted avg | 0.00 | 0.730082 | 0.692308 | 0.689867 | 208.000000 |
import time
start_time = time.perf_counter() # High-resolution start time
predicted_personality, scores = classificationModel.predict_single_image("../test_images/tom.jpg")
end_time = time.perf_counter() # High-resolution end time
elapsed_time_ms = (end_time - start_time) * 1000
print(f"Time taken for single prediction: {elapsed_time_ms:.3f} ms")
display(predicted_personality)
scores['Similarity Percentage'] = scores['Prediction Score'] * 100
scores_sorted = scores.sort_values(by='Similarity Percentage', ascending=False)
display(scores_sorted)
1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 142ms/step Time taken for single prediction: 200.044 ms
'tom hiddleston'
| Class Name | Class Index | Prediction Score | Similarity Percentage | |
|---|---|---|---|---|
| 0 | tom hiddleston | 47 | 9.609074e-01 | 9.609074e+01 |
| 1 | pedro alonso | 29 | 2.442909e-02 | 2.442909e+00 |
| 2 | josh radnor | 1 | 7.978412e-03 | 7.978413e-01 |
| 3 | mark ruffalo | 17 | 3.342980e-03 | 3.342980e-01 |
| 4 | johnny depp | 0 | 8.858606e-04 | 8.858606e-02 |
| 5 | robert downey jr | 36 | 8.476512e-04 | 8.476512e-02 |
| 6 | lionel messi | 10 | 5.609069e-04 | 5.609069e-02 |
| 7 | robert de niro | 35 | 3.321819e-04 | 3.321819e-02 |
| 8 | penn badgley | 30 | 1.682654e-04 | 1.682653e-02 |
| 9 | tom hardy | 46 | 1.194267e-04 | 1.194267e-02 |
| 10 | tom holland | 48 | 8.350729e-05 | 8.350729e-03 |
| 11 | richard harmon | 33 | 8.192172e-05 | 8.192171e-03 |
| 12 | tom ellis | 45 | 6.404772e-05 | 6.404771e-03 |
| 13 | rami malek | 31 | 6.239067e-05 | 6.239067e-03 |
| 14 | neil patrick harris | 28 | 6.203799e-05 | 6.203800e-03 |
| 15 | tom cruise | 44 | 2.510485e-05 | 2.510485e-03 |
| 16 | kiernen shipka | 5 | 1.384289e-05 | 1.384289e-03 |
| 17 | maisie williams | 13 | 5.641338e-06 | 5.641338e-04 |
| 18 | miley cyrus | 21 | 5.505120e-06 | 5.505120e-04 |
| 19 | keanu reeves | 4 | 5.402623e-06 | 5.402623e-04 |
| 20 | tuppence middleton | 49 | 4.416541e-06 | 4.416541e-04 |
| 21 | millie bobby brown | 22 | 3.819254e-06 | 3.819254e-04 |
| 22 | selena gomez | 39 | 1.614891e-06 | 1.614891e-04 |
| 23 | logan lerman | 11 | 1.366841e-06 | 1.366841e-04 |
| 24 | morgan freeman | 24 | 1.243366e-06 | 1.243366e-04 |
| 25 | maria pedraza | 15 | 8.610864e-07 | 8.610864e-05 |
| 26 | mark zuckerberg | 18 | 8.558867e-07 | 8.558867e-05 |
| 27 | leonardo dicaprio | 7 | 7.843571e-07 | 7.843571e-05 |
| 28 | katherine langford | 3 | 7.189742e-07 | 7.189742e-05 |
| 29 | nadia hilker | 25 | 6.466557e-07 | 6.466558e-05 |
| 30 | scarlett johansson | 38 | 5.123255e-07 | 5.123255e-05 |
| 31 | wentworth miller | 51 | 4.419033e-07 | 4.419033e-05 |
| 32 | madelaine petsch | 12 | 2.825000e-07 | 2.825000e-05 |
| 33 | natalie portman | 27 | 2.564185e-07 | 2.564185e-05 |
| 34 | stephen amell | 42 | 1.437359e-07 | 1.437359e-05 |
| 35 | natalie dormer | 26 | 1.192505e-07 | 1.192505e-05 |
| 36 | lili reinhart | 8 | 7.299278e-08 | 7.299278e-06 |
| 37 | sarah wayne callies | 37 | 4.732647e-08 | 4.732648e-06 |
| 38 | lindsey morgan | 9 | 3.512869e-08 | 3.512868e-06 |
| 39 | ursula corbero | 50 | 3.491779e-08 | 3.491779e-06 |
| 40 | rebecca ferguson | 32 | 1.687709e-08 | 1.687709e-06 |
| 41 | sophie turner | 41 | 1.352530e-08 | 1.352530e-06 |
| 42 | katharine mcphee | 2 | 1.139787e-08 | 1.139787e-06 |
| 43 | melissa fumero | 20 | 1.013638e-08 | 1.013638e-06 |
| 44 | margot robbie | 14 | 8.310916e-09 | 8.310915e-07 |
| 45 | taylor swift | 43 | 6.768491e-09 | 6.768491e-07 |
| 46 | shakira isabel mebarak | 40 | 6.251693e-09 | 6.251693e-07 |
| 47 | krysten ritter | 6 | 4.397424e-09 | 4.397424e-07 |
| 48 | marie avgeropoulos | 16 | 3.596515e-09 | 3.596515e-07 |
| 49 | megan fox | 19 | 1.266936e-09 | 1.266936e-07 |
| 50 | rihanna | 34 | 5.250642e-10 | 5.250642e-08 |
| 51 | morena baccarin | 23 | 3.322136e-10 | 3.322135e-08 |
Note here that the similariy percentage is shared between all the n classes. In strong similarity cases we can expect a similarity score of X% but it also means that the remaining will be shared between the N-1 classes and this is expected from a softmax layer output. We will discuss more about this as we go forward.
import pandas as pd
df = pd.read_csv("../SavedTrainingData/savedmodels/WLLM-Model-Nikhil-L2-12-10-01-24/TrainingTimeResults.csv")
display(df)
| Unnamed: 0 | Training Classes | TrainingTime | |
|---|---|---|---|
| 0 | 0 | 52 | 0 days 07:25:19.138662 |


from ClassificationModel import ClassificationModel
large_model_path = "../SavedTrainingData/savedmodels/WLLM-Model-Nikhil-C-12-09-22-11/best_model.keras"
names_csv_path = "../SavedTrainingData/savedmodels/WLLM-Model-Nikhil-C-12-09-22-11/WLLM-Model-Nikhil-C-12-09-22-11.csv"
image_dataset_path = "../dataset"
predictions_save_path = "../predictions/modelC"
classificationModel = ClassificationModel(large_model_path, names_csv_path)
Embedding model created using layer: 'embedding'.
classificationModel.evaluate_and_print_images("../TrainingDataImages/WLLM-Model-Nikhil-C-12-09-22-11/test")
Found 40 images belonging to 10 classes.
c:\Users\DELL\Desktop\Conestoga\AIML\FOML-FinalProject\WhoLooksLikeMe\venv\tensorflow_facenet\Lib\site-packages\keras\src\trainers\data_adapters\py_dataset_adapter.py:121: UserWarning: Your `PyDataset` class should call `super().__init__(**kwargs)` in its constructor. `**kwargs` can include `workers`, `use_multiprocessing`, `max_queue_size`. Do not pass these arguments to `fit()`, as they will be ignored. self._warn_if_super_not_called()
10/10 ━━━━━━━━━━━━━━━━━━━━ 5s 246ms/step
| accuracy | precision | recall | f1-score | support | |
|---|---|---|---|---|---|
| chris evans | 0.75 | 0.750000 | 0.75 | 0.750000 | 4.0 |
| chris hemsworth | 0.75 | 1.000000 | 0.75 | 0.857143 | 4.0 |
| chris pratt | 1.00 | 0.800000 | 1.00 | 0.888889 | 4.0 |
| christian bale | 1.00 | 0.666667 | 1.00 | 0.800000 | 4.0 |
| cristiano ronaldo | 0.75 | 1.000000 | 0.75 | 0.857143 | 4.0 |
| danielle panabaker | 1.00 | 1.000000 | 1.00 | 1.000000 | 4.0 |
| dominic purcell | 0.75 | 1.000000 | 0.75 | 0.857143 | 4.0 |
| dwayne johnson | 1.00 | 1.000000 | 1.00 | 1.000000 | 4.0 |
| eliza taylor | 1.00 | 1.000000 | 1.00 | 1.000000 | 4.0 |
| elizabeth lail | 1.00 | 1.000000 | 1.00 | 1.000000 | 4.0 |
| accuracy | 0.00 | 0.900000 | 0.90 | 0.900000 | 0.9 |
| macro avg | 0.00 | 0.921667 | 0.90 | 0.901032 | 40.0 |
| weighted avg | 0.00 | 0.921667 | 0.90 | 0.901032 | 40.0 |
import pandas as pd
df = pd.read_csv("../SavedTrainingData/savedmodels/WLLM-Model-Nikhil-C-12-09-22-11/TrainingTimeResults.csv")
display(df)
| Unnamed: 0 | Training Classes | TrainingTime | |
|---|---|---|---|
| 0 | 0 | 10 | 0 days 01:06:31.188613 |
Why this is important ?
from CosinePredictionHelper import CosinePredictionHelper
modelmap = {
"ModelA": "../SavedTrainingData/savedmodels/WLLM-Model-Nikhil-A-12-09-17-01", #Model A trained with first ten personalities in alphabetical order.
"ModelB": "../SavedTrainingData/savedmodels/WLLM-Model-Nikhil-B-12-09-20-24", #Model B trained with fnext 10
"ModelC": "../SavedTrainingData/savedmodels/WLLM-Model-Nikhil-C-12-09-22-11" #Model C trained with next 10
}
image_dataset_path = "../dataset"
predictions_save_path = "../predictions"
combinedCosinePredictor = CosinePredictionHelper(models=modelmap, N=5, image_dataset_path=image_dataset_path)
Embedding model created using layer: 'embedding'. Embedding model created using layer: 'embedding'. Embedding model created using layer: 'embedding'.
top_average, top_score = combinedCosinePredictor.run_pipeline("../test_images/lail.jpg", predictions_save_path)
../test_images/lail.jpg Total Remaining : 10 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 155ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 147ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 139ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 159ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 137ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 140ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 138ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 138ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 144ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 136ms/step ***************************************************** ***************************************************** Average scores: {'adriana lima': 0.7552034629978142, 'alex lawther': 0.7291574138313438, 'alexandra daddario': 0.7809922289458795, 'alvaro morte': 0.6710298529170245, 'alycia dabnem carey': 0.8062291955869716, 'amanda crew': 0.8075107267000539, 'amber heard': 0.8003184051134058, 'andy samberg': 0.7455171220479204, 'anne hathaway': 0.7903196199846573, 'anthony mackie': 0.6725007901870158} Total scores: {'adriana lima': 46, 'alex lawther': 31, 'alexandra daddario': 67, 'alvaro morte': 16, 'alycia dabnem carey': 92, 'amanda crew': 90, 'amber heard': 80, 'andy samberg': 44, 'anne hathaway': 70, 'anthony mackie': 14} ************************************************** Average Scores Sorted [('amanda crew', 0.8075107267000539), ('alycia dabnem carey', 0.8062291955869716), ('amber heard', 0.8003184051134058), ('anne hathaway', 0.7903196199846573), ('alexandra daddario', 0.7809922289458795), ('adriana lima', 0.7552034629978142), ('andy samberg', 0.7455171220479204), ('alex lawther', 0.7291574138313438), ('anthony mackie', 0.6725007901870158), ('alvaro morte', 0.6710298529170245)] Frequency Scores Sorted [('alycia dabnem carey', 92), ('amanda crew', 90), ('amber heard', 80), ('anne hathaway', 70), ('alexandra daddario', 67), ('adriana lima', 46), ('andy samberg', 44), ('alex lawther', 31), ('alvaro morte', 16), ('anthony mackie', 14)] ***************************************************** ../test_images/lail.jpg Total Remaining : 10 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 144ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 139ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 152ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 139ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 139ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 142ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 141ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 134ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 134ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 135ms/step ***************************************************** ***************************************************** Average scores: {'avril lavigne': 0.7982952474906956, 'barack obama': 0.7055718900001599, 'barbara palvin': 0.8141436216290703, 'ben affleck': 0.6555188646902484, 'bill gates': 0.7192064350063573, 'bobby morley': 0.6797838426491514, 'brenton thwaites': 0.7912064754726523, 'brian j. smith': 0.708207934623567, 'brie larson': 0.8394150175369706, 'camila mendes': 0.7588219721635066} Total scores: {'avril lavigne': 79, 'barack obama': 36, 'barbara palvin': 86, 'ben affleck': 10, 'bill gates': 47, 'bobby morley': 21, 'brenton thwaites': 73, 'brian j. smith': 37, 'brie larson': 99, 'camila mendes': 62} ************************************************** Average Scores Sorted [('brie larson', 0.8394150175369706), ('barbara palvin', 0.8141436216290703), ('avril lavigne', 0.7982952474906956), ('brenton thwaites', 0.7912064754726523), ('camila mendes', 0.7588219721635066), ('bill gates', 0.7192064350063573), ('brian j. smith', 0.708207934623567), ('barack obama', 0.7055718900001599), ('bobby morley', 0.6797838426491514), ('ben affleck', 0.6555188646902484)] Frequency Scores Sorted [('brie larson', 99), ('barbara palvin', 86), ('avril lavigne', 79), ('brenton thwaites', 73), ('camila mendes', 62), ('bill gates', 47), ('brian j. smith', 37), ('barack obama', 36), ('bobby morley', 21), ('ben affleck', 10)] ***************************************************** ../test_images/lail.jpg Total Remaining : 10 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 140ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 140ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 142ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 142ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 161ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 136ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 144ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 145ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 164ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 139ms/step ***************************************************** ***************************************************** Average scores: {'chris evans': 0.7102440640083643, 'chris hemsworth': 0.75016666041898, 'chris pratt': 0.6963686011032049, 'christian bale': 0.7019059148946654, 'cristiano ronaldo': 0.6831637687403139, 'danielle panabaker': 0.8286191067448486, 'dominic purcell': 0.6718353691328152, 'dwayne johnson': 0.7032357028691432, 'eliza taylor': 0.8010359258531172, 'elizabeth lail': 0.8457364129231838} Total scores: {'chris evans': 52, 'chris hemsworth': 62, 'chris pratt': 36, 'christian bale': 43, 'cristiano ronaldo': 28, 'danielle panabaker': 89, 'dominic purcell': 13, 'dwayne johnson': 46, 'eliza taylor': 81, 'elizabeth lail': 100} ************************************************** Average Scores Sorted [('elizabeth lail', 0.8457364129231838), ('danielle panabaker', 0.8286191067448486), ('eliza taylor', 0.8010359258531172), ('chris hemsworth', 0.75016666041898), ('chris evans', 0.7102440640083643), ('dwayne johnson', 0.7032357028691432), ('christian bale', 0.7019059148946654), ('chris pratt', 0.6963686011032049), ('cristiano ronaldo', 0.6831637687403139), ('dominic purcell', 0.6718353691328152)] Frequency Scores Sorted [('elizabeth lail', 100), ('danielle panabaker', 89), ('eliza taylor', 81), ('chris hemsworth', 62), ('chris evans', 52), ('dwayne johnson', 46), ('christian bale', 43), ('chris pratt', 36), ('cristiano ronaldo', 28), ('dominic purcell', 13)] *****************************************************
top_average, top_score = combinedCosinePredictor.run_pipeline("../test_images/alvaro.jpg", predictions_save_path)
../test_images/alvaro.jpg Total Remaining : 10 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 145ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 141ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 149ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 139ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 157ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 150ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 146ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 146ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 147ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 138ms/step ***************************************************** ***************************************************** Average scores: {'adriana lima': 0.7138186123543341, 'alex lawther': 0.7271488314488156, 'alexandra daddario': 0.6694106970404181, 'alvaro morte': 0.8304647378852088, 'alycia dabnem carey': 0.7260740585151053, 'amanda crew': 0.6980455482500423, 'amber heard': 0.6667116630203677, 'andy samberg': 0.7853243319796406, 'anne hathaway': 0.6682534670805661, 'anthony mackie': 0.7921371315828758} Total scores: {'adriana lima': 53, 'alex lawther': 60, 'alexandra daddario': 21, 'alvaro morte': 99, 'alycia dabnem carey': 64, 'amanda crew': 41, 'amber heard': 21, 'andy samberg': 86, 'anne hathaway': 20, 'anthony mackie': 85} ************************************************** Average Scores Sorted [('alvaro morte', 0.8304647378852088), ('anthony mackie', 0.7921371315828758), ('andy samberg', 0.7853243319796406), ('alex lawther', 0.7271488314488156), ('alycia dabnem carey', 0.7260740585151053), ('adriana lima', 0.7138186123543341), ('amanda crew', 0.6980455482500423), ('alexandra daddario', 0.6694106970404181), ('anne hathaway', 0.6682534670805661), ('amber heard', 0.6667116630203677)] Frequency Scores Sorted [('alvaro morte', 99), ('andy samberg', 86), ('anthony mackie', 85), ('alycia dabnem carey', 64), ('alex lawther', 60), ('adriana lima', 53), ('amanda crew', 41), ('alexandra daddario', 21), ('amber heard', 21), ('anne hathaway', 20)] ***************************************************** ../test_images/alvaro.jpg Total Remaining : 10 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 144ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 146ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 144ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 146ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 148ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 136ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 143ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 169ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 136ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 141ms/step ***************************************************** ***************************************************** Average scores: {'avril lavigne': 0.6550516486124576, 'barack obama': 0.7610881629676871, 'barbara palvin': 0.6943307861788807, 'ben affleck': 0.8024995985539279, 'bill gates': 0.7592740446343538, 'bobby morley': 0.8043018680525895, 'brenton thwaites': 0.7669554263679743, 'brian j. smith': 0.7562569705153827, 'brie larson': 0.7177858155266847, 'camila mendes': 0.7032858050606837} Total scores: {'avril lavigne': 10, 'barack obama': 63, 'barbara palvin': 23, 'ben affleck': 95, 'bill gates': 65, 'bobby morley': 95, 'brenton thwaites': 69, 'brian j. smith': 63, 'brie larson': 36, 'camila mendes': 31} ************************************************** Average Scores Sorted [('bobby morley', 0.8043018680525895), ('ben affleck', 0.8024995985539279), ('brenton thwaites', 0.7669554263679743), ('barack obama', 0.7610881629676871), ('bill gates', 0.7592740446343538), ('brian j. smith', 0.7562569705153827), ('brie larson', 0.7177858155266847), ('camila mendes', 0.7032858050606837), ('barbara palvin', 0.6943307861788807), ('avril lavigne', 0.6550516486124576)] Frequency Scores Sorted [('ben affleck', 95), ('bobby morley', 95), ('brenton thwaites', 69), ('bill gates', 65), ('barack obama', 63), ('brian j. smith', 63), ('brie larson', 36), ('camila mendes', 31), ('barbara palvin', 23), ('avril lavigne', 10)] ***************************************************** ../test_images/alvaro.jpg Total Remaining : 10 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 146ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 147ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 134ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 139ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 142ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 138ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 137ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 135ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 136ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 139ms/step ***************************************************** ***************************************************** Average scores: {'chris evans': 0.8129509737873967, 'chris hemsworth': 0.789883999219224, 'chris pratt': 0.7966906192232432, 'christian bale': 0.7870220700216634, 'cristiano ronaldo': 0.7830499023296358, 'danielle panabaker': 0.7392215487123732, 'dominic purcell': 0.800850999255398, 'dwayne johnson': 0.7815715672888071, 'eliza taylor': 0.7040024700367011, 'elizabeth lail': 0.7317640174171449} Total scores: {'chris evans': 94, 'chris hemsworth': 66, 'chris pratt': 79, 'christian bale': 60, 'cristiano ronaldo': 54, 'danielle panabaker': 32, 'dominic purcell': 81, 'dwayne johnson': 47, 'eliza taylor': 11, 'elizabeth lail': 26} ************************************************** Average Scores Sorted [('chris evans', 0.8129509737873967), ('dominic purcell', 0.800850999255398), ('chris pratt', 0.7966906192232432), ('chris hemsworth', 0.789883999219224), ('christian bale', 0.7870220700216634), ('cristiano ronaldo', 0.7830499023296358), ('dwayne johnson', 0.7815715672888071), ('danielle panabaker', 0.7392215487123732), ('elizabeth lail', 0.7317640174171449), ('eliza taylor', 0.7040024700367011)] Frequency Scores Sorted [('chris evans', 94), ('dominic purcell', 81), ('chris pratt', 79), ('chris hemsworth', 66), ('christian bale', 60), ('cristiano ronaldo', 54), ('dwayne johnson', 47), ('danielle panabaker', 32), ('elizabeth lail', 26), ('eliza taylor', 11)] *****************************************************
top_average, top_score = combinedCosinePredictor.run_pipeline("../test_images/sreehari.jpg", predictions_save_path)
../test_images/sreehari.jpg Total Remaining : 10 1/1 ━━━━━━━━━━━━━━━━━━━━ 3s 3s/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 149ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 150ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 137ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 135ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 142ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 132ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 135ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 131ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 135ms/step ***************************************************** ***************************************************** Average scores: {'adriana lima': 0.6464845691050131, 'alex lawther': 0.7584731672988688, 'alexandra daddario': 0.6643089328741357, 'alvaro morte': 0.7782157352269008, 'alycia dabnem carey': 0.6967903282887404, 'amanda crew': 0.7061726500822362, 'amber heard': 0.6230225440039927, 'andy samberg': 0.7819599009811565, 'anne hathaway': 0.6782800397293341, 'anthony mackie': 0.7718958093086739} Total scores: {'adriana lima': 21, 'alex lawther': 73, 'alexandra daddario': 31, 'alvaro morte': 91, 'alycia dabnem carey': 53, 'amanda crew': 55, 'amber heard': 12, 'andy samberg': 92, 'anne hathaway': 39, 'anthony mackie': 83} ************************************************** Average Scores Sorted [('andy samberg', 0.7819599009811565), ('alvaro morte', 0.7782157352269008), ('anthony mackie', 0.7718958093086739), ('alex lawther', 0.7584731672988688), ('amanda crew', 0.7061726500822362), ('alycia dabnem carey', 0.6967903282887404), ('anne hathaway', 0.6782800397293341), ('alexandra daddario', 0.6643089328741357), ('adriana lima', 0.6464845691050131), ('amber heard', 0.6230225440039927)] Frequency Scores Sorted [('andy samberg', 92), ('alvaro morte', 91), ('anthony mackie', 83), ('alex lawther', 73), ('amanda crew', 55), ('alycia dabnem carey', 53), ('anne hathaway', 39), ('alexandra daddario', 31), ('adriana lima', 21), ('amber heard', 12)] ***************************************************** ../test_images/sreehari.jpg Total Remaining : 10 1/1 ━━━━━━━━━━━━━━━━━━━━ 3s 3s/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 153ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 145ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 147ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 148ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 147ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 155ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 165ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 141ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 132ms/step ***************************************************** ***************************************************** Average scores: {'avril lavigne': 0.6588976332096701, 'barack obama': 0.7843169072676662, 'barbara palvin': 0.6787097841372003, 'ben affleck': 0.801008746411525, 'bill gates': 0.7384742151623434, 'bobby morley': 0.7883663236450413, 'brenton thwaites': 0.7645397771087815, 'brian j. smith': 0.7876602844767159, 'brie larson': 0.6951760204836428, 'camila mendes': 0.6425233320751266} Total scores: {'avril lavigne': 18, 'barack obama': 77, 'barbara palvin': 31, 'ben affleck': 92, 'bill gates': 50, 'bobby morley': 84, 'brenton thwaites': 65, 'brian j. smith': 82, 'brie larson': 37, 'camila mendes': 14} ************************************************** Average Scores Sorted [('ben affleck', 0.801008746411525), ('bobby morley', 0.7883663236450413), ('brian j. smith', 0.7876602844767159), ('barack obama', 0.7843169072676662), ('brenton thwaites', 0.7645397771087815), ('bill gates', 0.7384742151623434), ('brie larson', 0.6951760204836428), ('barbara palvin', 0.6787097841372003), ('avril lavigne', 0.6588976332096701), ('camila mendes', 0.6425233320751266)] Frequency Scores Sorted [('ben affleck', 92), ('bobby morley', 84), ('brian j. smith', 82), ('barack obama', 77), ('brenton thwaites', 65), ('bill gates', 50), ('brie larson', 37), ('barbara palvin', 31), ('avril lavigne', 18), ('camila mendes', 14)] ***************************************************** ../test_images/sreehari.jpg Total Remaining : 10 1/1 ━━━━━━━━━━━━━━━━━━━━ 2s 2s/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 132ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 166ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 158ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 142ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 153ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 137ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 154ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 138ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 124ms/step ***************************************************** ***************************************************** Average scores: {'chris evans': 0.8029547805821805, 'chris hemsworth': 0.7566127451244979, 'chris pratt': 0.7809077954243951, 'christian bale': 0.7475244210982548, 'cristiano ronaldo': 0.7756844375792936, 'danielle panabaker': 0.7215544321141862, 'dominic purcell': 0.7868324608506905, 'dwayne johnson': 0.7371024466346089, 'eliza taylor': 0.6906395878236402, 'elizabeth lail': 0.6917106245251968} Total scores: {'chris evans': 95, 'chris hemsworth': 60, 'chris pratt': 81, 'christian bale': 48, 'cristiano ronaldo': 75, 'danielle panabaker': 34, 'dominic purcell': 85, 'dwayne johnson': 40, 'eliza taylor': 15, 'elizabeth lail': 17} ************************************************** Average Scores Sorted [('chris evans', 0.8029547805821805), ('dominic purcell', 0.7868324608506905), ('chris pratt', 0.7809077954243951), ('cristiano ronaldo', 0.7756844375792936), ('chris hemsworth', 0.7566127451244979), ('christian bale', 0.7475244210982548), ('dwayne johnson', 0.7371024466346089), ('danielle panabaker', 0.7215544321141862), ('elizabeth lail', 0.6917106245251968), ('eliza taylor', 0.6906395878236402)] Frequency Scores Sorted [('chris evans', 95), ('dominic purcell', 85), ('chris pratt', 81), ('cristiano ronaldo', 75), ('chris hemsworth', 60), ('christian bale', 48), ('dwayne johnson', 40), ('danielle panabaker', 34), ('elizabeth lail', 17), ('eliza taylor', 15)] *****************************************************
top_average, top_score = combinedCosinePredictor.run_pipeline("../test_images/nikhil.jpg", predictions_save_path)
../test_images/nikhil.jpg Total Remaining : 10 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 197ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 145ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 136ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 160ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 168ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 163ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 141ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 157ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 146ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 147ms/step ***************************************************** ***************************************************** Average scores: {'adriana lima': 0.6373770698025024, 'alex lawther': 0.7173183755388431, 'alexandra daddario': 0.617166898138498, 'alvaro morte': 0.7443825179164236, 'alycia dabnem carey': 0.6518436915728826, 'amanda crew': 0.6306253974117697, 'amber heard': 0.613804717314867, 'andy samberg': 0.6919717722241882, 'anne hathaway': 0.6130849640213506, 'anthony mackie': 0.7102457581003344} Total scores: {'adriana lima': 44, 'alex lawther': 88, 'alexandra daddario': 24, 'alvaro morte': 97, 'alycia dabnem carey': 59, 'amanda crew': 41, 'amber heard': 22, 'andy samberg': 74, 'anne hathaway': 20, 'anthony mackie': 81} ************************************************** Average Scores Sorted [('alvaro morte', 0.7443825179164236), ('alex lawther', 0.7173183755388431), ('anthony mackie', 0.7102457581003344), ('andy samberg', 0.6919717722241882), ('alycia dabnem carey', 0.6518436915728826), ('adriana lima', 0.6373770698025024), ('amanda crew', 0.6306253974117697), ('alexandra daddario', 0.617166898138498), ('amber heard', 0.613804717314867), ('anne hathaway', 0.6130849640213506)] Frequency Scores Sorted [('alvaro morte', 97), ('alex lawther', 88), ('anthony mackie', 81), ('andy samberg', 74), ('alycia dabnem carey', 59), ('adriana lima', 44), ('amanda crew', 41), ('alexandra daddario', 24), ('amber heard', 22), ('anne hathaway', 20)] ***************************************************** ../test_images/nikhil.jpg Total Remaining : 10 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 153ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 137ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 131ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 149ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 152ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 153ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 158ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 146ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 156ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 151ms/step ***************************************************** ***************************************************** Average scores: {'avril lavigne': 0.5914019411362856, 'barack obama': 0.652860486208307, 'barbara palvin': 0.6286232985035607, 'ben affleck': 0.7308583024218456, 'bill gates': 0.6470643041051096, 'bobby morley': 0.7661884285373283, 'brenton thwaites': 0.6956500025111925, 'brian j. smith': 0.6604570837160469, 'brie larson': 0.6453119040916272, 'camila mendes': 0.6222438890417109} Total scores: {'avril lavigne': 10, 'barack obama': 55, 'barbara palvin': 33, 'ben affleck': 93, 'bill gates': 47, 'bobby morley': 97, 'brenton thwaites': 79, 'brian j. smith': 63, 'brie larson': 47, 'camila mendes': 26} ************************************************** Average Scores Sorted [('bobby morley', 0.7661884285373283), ('ben affleck', 0.7308583024218456), ('brenton thwaites', 0.6956500025111925), ('brian j. smith', 0.6604570837160469), ('barack obama', 0.652860486208307), ('bill gates', 0.6470643041051096), ('brie larson', 0.6453119040916272), ('barbara palvin', 0.6286232985035607), ('camila mendes', 0.6222438890417109), ('avril lavigne', 0.5914019411362856)] Frequency Scores Sorted [('bobby morley', 97), ('ben affleck', 93), ('brenton thwaites', 79), ('brian j. smith', 63), ('barack obama', 55), ('bill gates', 47), ('brie larson', 47), ('barbara palvin', 33), ('camila mendes', 26), ('avril lavigne', 10)] ***************************************************** ../test_images/nikhil.jpg Total Remaining : 10 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 148ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 125ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 126ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 135ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 135ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 130ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 136ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 135ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 134ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 131ms/step ***************************************************** ***************************************************** Average scores: {'chris evans': 0.726281781831082, 'chris hemsworth': 0.6942807134388362, 'chris pratt': 0.7185822028521882, 'christian bale': 0.7108857690420141, 'cristiano ronaldo': 0.6852512982873885, 'danielle panabaker': 0.6271865754214808, 'dominic purcell': 0.6873146799000256, 'dwayne johnson': 0.6853692542743464, 'eliza taylor': 0.6515792482996364, 'elizabeth lail': 0.6535641010655902} Total scores: {'chris evans': 95, 'chris hemsworth': 63, 'chris pratt': 88, 'christian bale': 82, 'cristiano ronaldo': 53, 'danielle panabaker': 12, 'dominic purcell': 55, 'dwayne johnson': 50, 'eliza taylor': 27, 'elizabeth lail': 25} ************************************************** Average Scores Sorted [('chris evans', 0.726281781831082), ('chris pratt', 0.7185822028521882), ('christian bale', 0.7108857690420141), ('chris hemsworth', 0.6942807134388362), ('dominic purcell', 0.6873146799000256), ('dwayne johnson', 0.6853692542743464), ('cristiano ronaldo', 0.6852512982873885), ('elizabeth lail', 0.6535641010655902), ('eliza taylor', 0.6515792482996364), ('danielle panabaker', 0.6271865754214808)] Frequency Scores Sorted [('chris evans', 95), ('chris pratt', 88), ('christian bale', 82), ('chris hemsworth', 63), ('dominic purcell', 55), ('cristiano ronaldo', 53), ('dwayne johnson', 50), ('eliza taylor', 27), ('elizabeth lail', 25), ('danielle panabaker', 12)] *****************************************************